The present invention relates to a method and system for forecasting the quantities of parts necessary to assemble vehicles for a vehicle product line.
The automotive industry is unique in that the automobile manufacturers sell a variety of high volume, constantly changing, and highly complex products. Most of the major automobile manufacturers carry between ten to twenty lines of vehicles. Many of these vehicle lines sell on the order of hundreds of thousands of vehicles per year.
The parts necessary for each vehicle can vary significantly from vehicle to vehicle. To begin with, each vehicle line typically offers more than one model. Also, each model typically offers about a hundred customer choices available among standard and optional features. As such, the manufacturing of any given vehicle line can require thousands of different vehicle parts.
Adding to the complicated process of manufacturing vehicles is that the vehicle manufacturer uses hundreds of different part suppliers to supply it with the parts required to manufacture the vehicles of a vehicle line. In order for the parts suppliers to be able to supply the automobile manufacturer""s assembly plants with the necessary parts at the necessary time, it is not uncommon for the parts supplier to require more than one year, and sometimes three or more years, of advanced notice of the parts and their volumes needed. Primarily, this is because the parts supplier requires a great deal of time to design and construct its parts manufacturing facilities. Thus, to provide reasonable assurance of being able to meet an automobile manufacturer""s future parts needs, part suppliers need accurate information from the automobile manufacturer about expected shipping volumes usually between one to three years in advance of the actual assembly of the finished vehicles.
The actual parts necessary for each vehicle can only be determined after a vehicle is ordered. The parts are determined, in large part, from the features that the consumer selects for his vehicle. However, since the parts manufacturer needs advance notice of the parts and their quantities usually at least a year in advance of production of the vehicles and since customers do not wish to wait much longer than a week or so for their vehicle once ordered, it is not feasible to wait until the orders have been completed before alerting a parts manufacturer as to what parts are needed.
Typically a sales department can reliably forecast, based on sales histories or intended promotions, the expected sales proportions of the individual features of a vehicle line (e.g., 30% of the vehicles to be assembled will have the air-conditioner feature). Any part used solely when a single feature is selected (e.g., a part that is used solely on all vehicles with air conditioners) would therefore get a reliable forecast by simply making the part forecast agree with the feature forecast.
However, many parts are required when two or more features are selected. Even if all of the individual features for these types of parts have been forecasted, the method used to forecast the likelihood that the combination of features will be selected is not accurate. Typically, a xe2x80x9crate-on-ratexe2x80x9d method is used. For parts requiring a combination of features, the forecasted percentages of these features are multiplied to ascertain the percent likelihood of the combination. This is done without taking any product rules (identification of restricted and required part combinations) into account. As such, these calculated estimates can, and tend to, be quite inaccurate.
Providing inaccurate information to the parts supplier can result in many problems. One problem, under estimating future demand, can result in lost sales for the automobile manufacturer because of insufficient capacity to supply parts needed for the assembly of vehicles. Another problem, resulting from over estimating demand is the loss associated with wasted facilities. Because of high volume frequently seen in the automotive industry, even the smallest miscalculation of future parts demand can translate into very large losses of capital.
Accordingly, what is needed is a method for accurately estimating the quantity of all the parts necessary for a vehicle product line at a time which is significantly in advance of the time that the parts are actually needed for assembly, and significantly in advance of receipt of any actual vehicle orders separated by vehicle customers.
Accordingly, it is an object of the present invention to provide a method for accurately forecasting the quantities of all the parts necessary for a vehicle product line. The method comprises inputting the available features and product rules for vehicle orders of the vehicle line into a computer data base, inputting sales forecasts for a first plurality of features of the vehicle line into the computer data base, randomly generating a substantial sample of vehicle orders based on the features, product rules, and the feature sales forecasts, and determining the quantity of all parts necessary to assemble all vehicles of a vehicle product line for a predetermined time period based on the sample order.
The present invention also provides a system for accurately and reliably forecasting the quantities of all the parts necessary for a vehicle product line. The system comprises a storage device operable to store permanent data, a memory device operable to store a computer program and temporary data, an input device operable to provide an interface with the system to input available features and product rules for vehicle orders of a vehicle line and sales forecasts for a first plurality of features for a vehicle line, an output device operable to provide an interface with the system to output the quantity of all parts necessary to assemble all vehicles of a vehicle product line for a predetermined time period parts available, and a processor coupled to the storage device, the memory device, and the input and output devices. The processor operates to execute the computer program such that the system is directed to randomly generate a substantial sample of vehicle orders based on the features, product rules and the feature sales forecasts, and determine the quantity of all parts necessary to assemble all vehicles of a vehicle product line for a predetermined time period based on the sample orders.